%0 Journal Article
%T Quantum-behaved particle swarm optimization with diversity-guided mutation<br>基于多样性变异的量子行为粒子群优化算法
%A LONG Hai-xi
%A MA Sheng-quan
%A <br>龙海侠
%A 马生全
%J 计算机应用研究
%D 2011
%I 
%X To overcome the premature convergence of quantum-behaved particle swarm optimization(QPSO) algorithm,this paper proposed QPSO with diversity-guided mutation(QPSO-DGM) to improve the performance of QPSO.In the proposed QPSO-DGM algorithm,set diversity function.When the value of diversity was less during the search,operated the mutation.QPSO-DGM made the particles' search scope expanded and avoided the declination of population diversity.The experiment results on benchmark functions show that both QPSO-DGM ha...
%K Quantum-behaved particle swarm optimization algorithm
%K diversity-guided mutation
%K diversity function
%K benchmark functions<br>量子行为的粒子群优化算法
%K 多样性变异
%K 多样性函数
%K 标准函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=51CC87573FE33A0FA81DAD9A061CE3EE&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=B31275AF3241DB2D&sid=13AD3798DE81DFD6&eid=ADC771006BF99B57&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12